Getting Rid of Dichotomous Sex Estimations: Why Logistic Regression Should be Preferred Over Discriminant Function Analysis

Sex estimation is an important part of creating a biological profile for skeletal remains in forensics. The commonly used methods for developing sex estimation equations are discriminant function analysis (DFA) and logistic regression (LogR). LogR equations provide a probability of the predicted sex, while DFA relies on cutoff points to segregate males and females, resulting in a rigid dichotomization of the sexes. This is problematic because sexual dimorphism exists along a continuum and there can be considerable overlap in trait expression between the sexes. In this study, we used humeral measurements to compare the performance of DFA and LogR and found them to be very similar under multiple conditions. The overall cross-validated (leave-one-out) accuracy of DFA (75.76–95.14%) was slightly higher than LogR (75.76–93.82%) for simple and multiple variable equations, and also performed better under varying sample sizes (94.03% vs. 93.78%). Three of five DFA equations outperformed LogR under the B index, while all five LogR equations outperformed the DFA equations under the Q index. Both methods saw an improvement in overall accuracy (DFA: 86.74–95.79%; LogR: 86.74–95.76%) when individuals with a classification probability lower than 0.80 were excluded. Additionally, we propose a method for calculating additional cutoff points (PMarks) based on posterior probability values. In conclusion, we recommend using LogR over DFA due to the increased flexibility, robusticity, and benefits for future users of the statistical models; however, if DFA is preferred, use of the proposed PMarks facilitates future analysis while avoiding unnecessary dichotomization.     

Understanding research methods,limitations, and applications of drug data collected by the National Forensic Laboratory Information System (NFLIS-Drug)

The National Forensic Laboratory Information System (NFLIS) is a drug surveillance program of the US Drug Enforcement Administration that systematically collects data on drugs that are seized by law enforcement and submitted to and analyzed by the Nation's forensic laboratories (NFLIS-Drug). NFLIS-Drug data are increasingly used in predictive modeling and drug surveillance to examine drug availability patterns. Given the complexity of the data and data collection, there are some common methodological pitfalls that we highlight with the aim of helping researchers avoid these concerns. The analysis done for this Technical Note is based on a review of the scientific literature that includes 428 unique, refereed article citations in 182 distinct journals published between January 1, 2005, and April 30, 2021. Each article was analyzed according to how NFLIS-Drug data were mentioned and whether NFLIS-Drug data were included. A sample of 37 articles was studied in-depth, and data issues were summarized. Using examples from the literature, this Technical Note highlights eight broad concerns that have important implications for the proper applications, interpretations, and limitations of NFLIS-Drug data with suggestions for improving research methods and accurate reporting of forensic drug data. NFLIS-Drug data are timely and provide key information to inform drug use trends across the United States; however, our present analysis shows that NFLIS-Drug data are misunderstood and represented in the literature. In addition to highlighting these issues, DEA has created several resources to assist NFLIS data users and researchers, which are summarized in the discussion.     

Identifying reliable ions for the statistical differentiation of structurally similar fentanyl analogs

Definitive identification of fentanyl analogs based on mass spectral comparison is challenging given the high degree of structural and, hence, spectral similarity. To address this, a statistical method was previously developed in which two electron-ionization (EI) mass spectra are compared using the unequal variance t-test. Normalized intensities of corresponding ions are compared, testing the null hypothesis (H₀) that the difference in intensity is equal to zero. If H₀ is accepted at all m/z values, the two spectra are statistically equivalent at the specified confidence level. If H₀ is not accepted at any m/z value, then there is a significant difference in intensity at that m/z value between the two spectra. In this work, the statistical comparison method is applied to distinguish EI spectra of valeryl fentanyl, isovaleryl fentanyl, and pivaloyl fentanyl. Spectra of the three analogs were collected over a 9-month period and at different concentrations. At the 99.9% confidence level, the spectra of corresponding isomers were statistically associated. Spectra of different isomers were statistically distinct, and ions responsible for discrimination were identified in each comparison. To account for inherent instrument variations, discriminating ions for each pairwise comparison were ranked based on the magnitude of the calculated t-statistic (t_calc) value. For a given comparison, ions with higher t_calc values are those with the greatest difference in intensity between the two spectra and, therefore, are considered more reliable for discrimination. Using these methods, objective discrimination among the spectra was achieved and ions considered most reliable for discrimination of these isomers were identified.     

An unusual blunt force trauma pattern and mechanism to the cranial vault: Investigation of an atypical infant homicide

This case report presents an unusual fracture pattern in the cranium of a four-month-old infant indicative of child abuse. Upon postmortem examination, the infant presented with numerous bilateral linear cranial fractures running perpendicular to the sagittal suture with depressed and curvilinear fractures apparent on the supra-auricular surfaces of the cranium. Histological evidence indicates multiple traumatic events to the cranium. In addition, the stair-step pattern of a parietal fracture may represent multiple contiguous fractures from repeated loading of the head at different times with variation of the focal points of compressive force. Additionally, the left humerus, left radius, and left ulna have healing metaphyseal fractures, and the left ulna also has an antemortem diaphyseal fracture which resulted in the distal metaphysis being rotated 45 degrees medially. Integration of autopsy, anthropological, and neuropathological reports for this case suggest multiple inflicted injury episodes with a repeated atypical mechanism(s) to the cranial vault of the infant. During investigative interviews, the caretaker admitted to squeezing the infant's head and neck on multiple occasions to quiet the child. This reported abusive mechanism is consistent with the pattern of symmetric cranial fractures and soft tissue injuries indicating asphyxiation. This case report provides forensic investigators with a potential trauma mechanism to explore in cases when a similar pattern of cranial trauma is observed and highlights the need for greater research on fracture propagation and fracture healing in the infant cranium.     

Validation of the 4‐aminophenol color test for the differentiation of marijuana‐type and hemp‐type cannabis

The analysis of cannabis plant material submitted to seized‐drug laboratories was significantly affected by the signing of the Agricultural Improvement Act of 2018, which defined hemp and removed it from the definition of marijuana in the Controlled Substances Act. As a result, field law enforcement personnel and forensic laboratories now are in need of implementing new protocols that can distinguish between marijuana‐type and hemp‐type cannabis. Colorimetric tests provide a cost‐effective and efficient manner to presumptively identify materials prior to submission to a laboratory for analysis. This work presents the validation of the 4‐aminophenol (4‐AP) color test and demonstrates its utility for discriminating between marijuana‐type and hemp‐type cannabis (i.e., typification). Validation studies included the testing of numerous cannabinoid reference materials, household herbs, previously characterized cannabis plant samples, and real‐case samples. The 4‐AP test reliably produces a pink result when the level of Δ⁹‐tetrahydrocannabinol (THC) is approximately three times lower than the level of cannabidiol (CBD). A blue result is generated when the level of THC is approximately three times higher than that of CBD. Inconclusive results are observed when the levels of THC and CBD are within a factor of three from each other, demonstrating the limitations of the test under those scenarios.     

The Achilles Heel of Plurality Systems: Geography and Representation in Multiparty Democracies

Building on the unfinished research program of Gudgin and Taylor (1979), we analytically derive the linkage between a party's territorial distribution of support and the basic features of its vote‐seat curve. We then demonstrate the usefulness of the corresponding empirical model with an analysis of elections in postwar Great Britain, focusing in particular on the transformation of the Liberals from a territorially concentrated to a dispersed party in the 1970s. We show that majoritarian biases increase with the number of parties, and majoritarian systems harm small parties when their vote is more dispersed than average, and large parties when their vote is more concentrated than average. Moreover, the evolving experiences of Labour and Conservatives demonstrate how a party's territorial support, and hence its expected seat premium or penalty, changes with its electoral fortunes. This model has a wide variety of applications in multiparty majoritarian democracies around the world.